Publications by authors named "Desir C"

Background: Interstitial lung diseases (ILDs) are an heterogeneous group of infiltrating lung pathologies, for which prompt diagnosis and continuous assessment are of paramount importance. While chest CT is an established diagnostic tool for ILDs, there are no formal guidelines on the follow-up regimen, leaving the frequency and modality of follow-up largely at the clinician's discretion.

Methods: The study retrospectively evaluated the indication of chest CT in a cohort of 129 ILD patients selected from the ambulatory care polyclinic at University Hospital of Liège.

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Background: The prediction of the individual insulin needs may facilitate the initiation of insulin therapy. Our aim was to explore the relationships between body weight, sex, and daily amounts of insulin delivered by a hybrid closed-loop system.

Methods: We performed a retrospective data collection of all consenting adult patients with type 1 diabetes who were equipped in Europe with the Diabeloop Generation 1 (DBLG1) hybrid closed-loop insulin delivery device between March 1, 2021 and February 28, 2023.

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Background And Objective: Rheumatoid arthritis associated-interstitial lung disease (RA-ILD) is the most common pulmonary manifestation of rheumatoid arthritis (RA) and an important cause of mortality. In patients suffering from interstitial lung diseases (ILD) from different etiologies (including RA-ILD), a significant proportion is exhibiting a fibrotic progression despite immunosuppressive therapies, defined as progressive fibrosing interstitial lung disease (PF-ILD). Here, we report the frequency of RA-ILD and PF-ILD in all RA patients' cohort at University Hospital of Liège and compare their characteristics and outcomes.

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The aim of this study was to better characterise whether sleep habits, eating schedule and physical activity in real-life are associated with glycaemic control in patients with type 2 diabetes. A total of 28 patients (aged 60 years [58; 66], 54% female) with type 2 diabetes treated with basal-bolus insulin therapy administered by insulin pumps were analysed. Glycaemic data measured by Flash Glucose Monitor System, physical activity and sleep data measured by accelerometer, and meal schedules were simultaneously collated with insulin pump administration data, for 7 days in real-life.

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During the COVID-19 pandemic induced by the SARS-CoV-2, numerous chest scans were carried out in order to establish the diagnosis, quantify the extension of lesions but also identify the occurrence of potential pulmonary embolisms. In this perspective, the performed chest scans provided a varied database for a retrospective analysis of non-COVID-19 chest pathologies discovered de novo. The fortuitous discovery of de novo non-COVID-19 lesions was generally not detected by the automated systems for COVID-19 pneumonia developed in parallel during the pandemic and was thus identified on chest CT by the radiologist.

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Background: Patients suffering from combined obstructive and interstitial lung disease (O-ILD) represent a pathological entity which still has to be well clinically described. The aim of this descriptive and explorative study was to describe the phenotype and functional characteristics of a cohort of patients suffering from functional obstruction in a population of ILD patients in order to raise the need of dedicated prospective observational studies and the evaluation of the impact of anti-fibrotic therapies.

Methods: The current authors conducted a retrospective study including 557 ILD patients, with either obstructive (O-ILD, n = 82) or non-obstructive (non O-ILD, n = 475) pattern.

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Objectives: Various symptoms and considerable organ dysfunction persist following infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Uncertainty remains about the potential mid- and long-term health sequelae. This prospective study of patients hospitalized with coronavirus disease 2019 (COVID-19) in Liège University Hospital, Belgium aimed to determine the persistent consequences of COVID-19.

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Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50 years. As modern medicine is evolving towards precision medicine, offering personalized patient care and treatment, the requirement for robust imaging biomarkers has gradually increased. Radiomics, a specific method generating high-throughput extraction of a tremendous amount of quantitative imaging data using data-characterization algorithms, has shown great potential in individuating imaging biomarkers.

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Background And Purpose: Radiation recall pneumonitis (RRP) is a delayed radiation-induced lung toxicity triggered by systemic agents, typically anticancer drugs. Immune checkpoint inhibitors (ICIs) have recently been identified as potential causal agents of RRP but its real incidence and potential risk factors remain unknown.

Materials And Methods: Medical records and CTs of patients treated with programmed death 1 (PD-1) or programmed death ligand 1 (PD-L1) inhibitors for advanced lung cancer between 2014 and 2019 at our tertiary center, and who had a previous history of lung irradiation were retrospectively analyzed.

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The daily challenge for people with type 1 diabetes is maintaining glycaemia in the "normal" range after meals, by injecting themselves the correct amount of insulin. Artificial pancreas systems were developed to adjust insulin delivery based on real-time monitoring of glycaemia and meal patient's report. Meal reporting is a heavy burden for patients as it requires carbohydrate estimation several times per day.

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The subpleural arteriovenous shunts that are hallmarks of hepatopulmonary syndrome may cause stroke.

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Crohn's disease is a chronic inflammatory condition characterized by recurrent and/or chronic lesions, leading to cumulative structural bowel damage. It is established that the correlation between symptoms and intestinal lesions is weak. Therefore, monitoring by frequent cross-sectional imaging is proposed to assess the disease activity.

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This paper presents a conformable wireless patch and its mobile application for physical activity, spO2 and pCO2 recording associated to digital biomarkers that aim at providing the clinicians with a reliable computer-aided diagnosis tool for rapid and continuous monitoring of sleep respiratory disorders. Each part of the system is described and results are presented and discussed. The reflectance sp02 sensor has been tested in vivo on several body sites and several subjects then compared to a reference device.

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Adolescents are an emerging population in Haiti, particularly after the deadly 2010 earthquake. The steady penetration of U.S.

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Recently, the in vivo imaging of pulmonary alveoli was made possible thanks to confocal microscopy. For these images, we wish to aid the clinician by developing a computer-aided diagnosis system, able to discriminate between healthy and pathological subjects. The lack of expertise currently available on these images has first led us to choose a generic approach, based on pixel-value description of randomly extracted subwindows and decision tree ensemble for classification (extra-trees).

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A novel imaging technique can now provide microscopic images of the distal lung in vivo, for which quantitative analysis tools need to be developed. In this paper, we present an image classification system that is able to discriminate between normal and pathological images. Different feature spaces for discrimination are investigated and evaluated using a support vector machine.

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